Blog posts tagged with 'big data''

2016-10-15: This article is part 1 of an upcoming article series, Storm vs. Heron.

2016-12-02: This article is part 2 of an upcoming article series, Storm vs. Heron.

2019-04-11: In this article, I’ll document my process of building a home server - or NAS - for local storage, smb drives, backups, processing, git, CD-rips, and other headless computing...

2019-07-01: In this article, we'll take a look at whether Apache Hadoop still a viable option in 2019, with Cloud driven data processing an analytics on the rise...

2019-12-09: The amount of time my outdoor cameras are being set off by light, wind, cars, or anything other than a human is insane. Overly cautious security cameras might be a feature, but an annoying one at that...

2018-06-12: In this article (and its successors), we will use a fully serverless Cloud solution, based on Google Cloud, to analyze the top Reddit posts of the 100 most popular subreddits. We will be looking at images, text, questions, and metadata...

2018-03-18: In this article, we will use Heron, the distributed stream processing and analytics engine from Twitter, together with Google’s NLP toolkit, Nominatim and some Machine Learning as well as Google’s BigTable, BigQuery, and Data Studio to plot Twitter user's assumed location across the US.

2018-10-27: In the last iteration of this article we analyzed the top 100 subreddits and tried to understand what makes a reddit post successful by using Google’s Cloud ML tool set to analyze popular pictures.

2017-11-04: This article will talk about how organizations can make use of the wonderful thing that is commonly referred to as “Data Lake” - what constitutes a Data Lake, how probably should (and shouldn’t) use it to gather insights and why evaluating technologies is just as important as understanding your data...

2021-02-28: On the joy of inheriting a rather bad dataset - dissecting ~120GB of terrible Google Takeout data to make it usable, using Dataflow/Beam, go, Python, and SQL.

2021-12-03: How I build what is essentially a self-service Data Lake at home to narrow down the search area for a new house, instead of using Zillow like a normal person, using Spark, Iceberg, and Python.

2020-07-06: In Part 2 of our comparison of Python and go from a Data Engineering perspective, we'll finally take a look at Apache Beam and Google Dataflow and how the go SDK and the Python SDK differ, what drawbacks we're dealing with, how fast it is by running extensive benchmarks, and how feasible it is to make the switch

2020-06-11: Exploring golang - can we ditch Python for go? And have we finally found a use case for go? Part 1 explores high-level differences between Python and go and gives specific examples on the two languages, aiming to answer the question based on Apache Beam and Google Dataflow as a real-world example.